The belief that public schools produce better integration than
private schools is deeply held by many people, but it is unfortunately supported by little
empirical evidence. In this paper we take a systematic look at integration in a random
sample of public and private schools in two cities. Unlike previous studies of integration
in schools, our data are drawn from a setting in which racial mixing has greater meaning:
the lunchroom. We also develop new measures of integration that allow for easier, more
meaningful comparisons between different school systems. Our analyses suggest that private
schools tend to offer a more racially integrated environment than do public schools. The
primary explanation for private schools success at integration is that private
school attendance is not as closely attached to where one lives as attendance at public
schools. Public schools tend to replicate and reinforce racial segregation in housing.
Because private schools do not require that their students live in particular
neighborhoods, they can more easily overcome segregation in housing to provide integration
in school. The strong religious mission and higher social class found in most private
schools are also factors that contribute to better racial integration.

Since Horace Manns description of the common
school, one of the stated goals of American education has been to bring students of
different backgrounds together in schools. The belief that
government-operated schools would mix students better than private schools was one of the
primary justifications for the development and growth of a universal system of public
schools. As Secretary of Education Riley recently argued, The common
school -- the concept upon which our public school system was built -- teaches
children important lessons about both the commonality and diversity of American culture.
These lessons are conveyed not only through what is taught in the classroom, but by the
very experience of attending school with a diverse mix of students. The common school has
made quality public education and hard work the open door to American success and good
citizenship and the American way to achievement and freedom. (Riley, 1997, p. 1)
While public control and government-operation of schools has been thought to be essential
for producing integrated education, privately-run schools, based on the voluntarily
association of individuals, have generally been held as not conducive to integration.

The belief that public schools produce better integration than
private schools is deeply held by many people, but it is unfortunately supported by little
empirical evidence. In this paper we take a systematic look at integration in a random
sample of public and private schools in two cities. Unlike previous studies of integration
in schools, our data are drawn from a setting in which racial mixing has greater meaning:
the lunchroom. We also develop new measures of integration that allow for easier, more
meaningful comparisons between different school systems. Our analyses suggest that private
schools tend to offer a more racially integrated environment than do public schools. The
primary explanation for private schools success at integration is that private
school attendance is not as closely attached to where one lives as attendance at public
schools. Public schools tend to replicate and reinforce racial segregation in housing.
Because private schools do not require that their students live in particular
neighborhoods, they can more easily overcome segregation in housing to provide integration
in school. The strong religious mission and higher social class found in most private
schools are also factors that contribute to better racial integration.

Defining and Measuring Integration

We care about integration in schools for a variety of reasons. As
the Supreme Court observed in its 1954 Brown v. Board of Education decision,
segregated schools raise serious concerns that the separate education received by
different groups is unlikely to be equal. School policies aimed at reducing segregation,
such as bussing and magnet programs, seek integration as a way to eliminate disparities in
the quality of education provided to different racial and ethnic groups. But our hopes for
integration go beyond avoiding segregation and unequal schools. Racial integration in
schools has also been pursued to provide students with the experience of interacting with
people who are different from them as an important educational goal in its own right. Our
hope is that this proximity will help students learn about different kinds of people and
become more tolerant of those differences.

A considerable amount of research has examined the extent to
segregated schools are unequal in the quality of their academics, the extent to which
mutual understanding and tolerance are promoted by integration, and the extent to which
bussing, magnets and other policies have succeeded in integrating schools (Schofield 1997,
Yu and Taylor 1997, Taylor and Rickel 1981, Orfield et. al 1996, Rossell 1990, Armor 1995,
Oakes 1985, Hochschild 1984, Crain, Mahard, and Narot 1982). These issues are not the ones
directly addressed in this paper. For our purposes we will assume that racial integration
in schools is a desirable goal. The question we address is whether public or private
schools are different in their ability to achieve integration.

Unfortunately, commonly used measures of integration were developed
largely to address legal disputes about whether school systems are segregated and
therefore whether they could be assumed to be providing different, and unequal,
educational experiences to different groups. These measures were not used to address
whether schools offer a positive integrated experience for those groups. Conventional
measures, such as The Index of Dissimilarity (IOD) for example, do not focus on how likely
it is that students will have the ability to meet and learn from students of different
racial or ethnic backgrounds. Instead, the Index of Dissimilarity simply measures how
evenly groups are distributed within a school system. A school system
that was 98% white would receive the highest score on the IOD if every school in that
system were also 98% white, simply because whites and non-whites were perfectly evenly
distributed. This measure would help us address the legal question of whether the school
system was segregating a group of students with a presumably inferior education. But the
perfect score generated by this measure does not tell us whether students in that school
system are likely to come into contact with different types of students, an experience
from which they might gain mutual understanding (Rossell 1990).

Another common measure, the Index of Exposure (IOE), is designed to
address this problem by calculating the average percentage of one racial or ethnic group
in the same school as the average member of another group. Using the
example above, the IOE could be used to calculate that the average white student had 2%
non-whites in the same school and the average non-white student had 98% white students in
the same school. One difficulty with this measure is that the IOE changes depending on
which group is the focus of examination. The IOE is 2, for example, if we want to know the
exposure of whites to others, yet the same district has a score of 98 if we want to know
the exposure of non-whites to others. That is, the IOE would say that integration is lousy
in this hypothetical school system if you are white and wonderful if you are non-white
(Crain 1984). But what if we wanted to know how well the school system is integrated in
general? Or how could we compare this school system to another one with a different racial
composition, one that was 50 percent white and 50 percent non-white for example? The IOE
does not adequately address these questions. It is also limited by the fact that it can
only measure exposure between two groups, thus not allowing an adequate analysis of
multi-ethnic integration.

Sometimes researchers present a standardized IOE as a measure of the
overall integration in a school system. To standardize the IOE, the
racial composition of the whole school system must be taken as a given. That is, the
standardized IOE could tell us an overall measure of integration for our hypothetical
school system given the fact that it has 98% whites and 2% non-whites. However,
standardization just reintroduces the problems of the Index of Dissimilarity. The
standardized IOE would tell us that our nearly homogeneous hypothetical school system is
well integrated given that it is nearly homogenous in its racial composition. But how
could we meaningfully compare this overall measure of integration to another school system
that had more minority students but distributed them less than perfectly evenly? The
standardized IOE would tell us that integration is better in the more homogeneous system
with perfectly even distribution than in the more racially heterogeneous school system
with a less than perfectly even distribution. Because the standardized IOE takes the
racial composition of the system as a given, it shares the IODs defect of describing
evenly distributed but racially homogenous school systems as well integrated.

These measures of integration also suffer from the problem of
measuring inputs not outputs. The Index of Dissimilarity and the Index of Exposure only
measure the extent to which different racial groups are in the same school building; they
do not measure the extent to which those groups are in the same classrooms, get to know
each other, and learn to like each other. The former is sufficient for addressing the
legal questions of whether the school system provides the same quality of education to
different racial or ethnic groups, but it is inadequate for addressing the extent to which
the system achieves the positive socialization of an integrated experience. The
introduction of different groups of students into a school is an input; learning and
mutual understanding is an output. If we want to know how well schools achieve the ideals
of the common school we should have a measure of integration that more closely captures
that output.

In the early 1980s, James Coleman and colleagues (1982)
employed a measure similar to the Index of Dissimilarity to determine whether public or
private schools were better racially integrated. Their conclusion was that private schools
were better integrated because the distribution of racial groups was more even there than
in public schools. Taeuber and James (1982) and Page and Keith (1981) responded that
private schools should not be described as contributing to integration because they have a
lower percentage of minority students, on average, than do public schools. That is, they
argued that private schools may have a more even distribution of minorities, but the
general lack of minority students makes them relatively racially homogenous, not
integrated. In 1984, Robert Crain employed the Index of Exposure in a comparison of
Catholic and public schools in Cleveland and Chicago and concluded that Catholic high
schools were better racially integrated than their public school counterparts. But his
study is limited by the difficulties of conventional measures, and the fact that he
examined only Catholic private schools which, while a large portion of all private
schools, may produce results that are atypical of the universe of private schools. More
recently, Jay Greene (1998) examined a national sample of public and private school
classrooms to determine which tended to be closer to the national proportion of minority
students. He concluded that private school classrooms, on average, were more
representative of the national minority proportion than were public school classrooms, on
average. But measuring the proportions of racial groups in classrooms is still a measure
of the inputs of integration, not the output of successful racial exposure.

A New Measure of Integration

In this study we employ a new measure of integration, which we call
the Index of Integration (IOI), that we believe better captures the extent of positive
socialization resulting from racial integration. Quite simply, we observed school
lunchrooms and recorded where students sat by race. We then calculated the percentage of
students who had a student of a different racial group sitting next to them. We define
sitting next to a person as sitting to the right, left, across, across and to the right,
or across and to the left of the observed student. If any of those five seats was occupied
by a student of a different racial group, then the observed student was coded as having an
integrated lunchroom setting. From this, the percentage of students who have an integrated
lunchroom setting can be calculated for an entire school system.

This Index of Integration does not focus on how evenly students are
distributed in a school system nor does it adjust for the homogeneous or heterogeneous
character of the system, as do the IOD and standardized IOE. For our purposes we do not
want to know whether school systems evenly distribute the racial groups they have.
Although if a system is racially homogenous or unevenly distributes racial groups,
students will have fewer students of another race with which they can mix in the lunchroom
and thus this information does weigh into the score. Our goal, however, is to determine
whether students ultimately have a positive, heterogeneous racial experience. In everyday
usage, this is typically what we mean by integration. Do students have the experience of
mixing with students of different backgrounds in a positive way?

Unlike the unstandardized Index of Exposure, this new measure does
not generate different results depending on which racial group we choose to consider. The
IOI looks at whether students sit next to students who are different, regardless of
whether the student is African-American, white, Hispanic, or Asian. And the IOI is better
in that it captures multi-ethnic integration more accurately by counting students in
heterogeneous lunch settings regardless of which combination of racial groups produces
that heterogeneity.

The Index of Integration also allows for more meaningful comparisons
between school systems. If we want to compare integration in public and private
school systems in the same area, we ought not to adjust for the racial compositions of
those sectors. The racial composition of the sector is precisely what has a great
influence on whether individual students are likely to have an integrated experience. To
say that one school system is better integrated than another because it evenly distributes
its racially homogenous population has little relationship to whether that school system
actually offers a better integration experience. The IOI tells us whether students in
public or private school systems in the same area are more likely to sit in racially
heterogeneous groups; that tells us the system in which students are more likely to
experience positive integration.

Lastly, the IOI has the advantage of more closely measuring the
outcome of integration as opposed to the inputs. Schools are producing successful
integration when students of different racial backgrounds are comfortable enough to sit
next to each other in the informal setting of the lunchroom. Students of different
backgrounds may be in the same school buildings but become re-segregated through tracking
(Oakes 1985). Students of different backgrounds may even share the same classrooms, but
fail to get to know each other, learn about each other, or gain mutual respect and
understanding (Gadsden, Smith, and Jordan 1996, Grant 1990). But the lunchroom is where
the race-relations rubber meets the road. We can have greater confidence that
students are having a positive integrated experience if they choose to sit near each other
in the lunchroom.

To be sure there are limitations to this approach to measuring
integration. Collecting the data is labor intensive, involving the observation of scores
of lunchrooms. Obtaining permission and scheduling visits took months in this project.
Accurately identifying students racial groups by their appearance also involves
possible error. Race is a social construct, not an easily measured set of physical traits.
But we have confidence that this error is minimal because the proportions of racial groups
that we identified by observation matched the proportions in the data provided by schools
based on self-identification of race. The Index of Integration is also sensitive to the
racial categories that are considered. In this study we coded students as white,
African-American, Latino, or Asian. Because race is a social construct, we could have
split these categories more finely or combined some of them. We chose these categories
because they are the ones around which people tend to organize themselves and therefore
are considered politically relevant. Another potential weakness of the IOI is that it may
cast the net too broadly by counting a student as having an integrated lunchroom setting
if any one of the five students around him or her is of a different racial group. This
broad definition may elevate the measure of integration for all schools, but it is
unlikely to bias the comparison between school systems. In fact, the results of this study
are not dependent on the particular way we have defined an integrated lunchroom setting;
the race of the student or students to the right or across from the observed student could
have been used instead with the same results. While any measure of integration will have
some shortcomings, the one used in this study appears well suited to capturing the
comparative extent to which public and private schools in the same area produce a positive
integrated experience for their students.

The Sample

A randomly drawn sample of public and private schools in two cities
provided subjects for this study. (The identity of the two cities is being kept
confidential until reports can be prepared and reviewed by the public school officials in
those cities.) In each city ten public schools were drawn from a universe of all public
schools in those cities. Also in each city ten private schools were drawn from a universe
of all private schools in those cities. The universe of private schools was identified by
compiling a list from phone books and the Catholic Archdiocese. Data ultimately were
collected from 38 (19 public and 19 private) schools due to difficulty gaining permission
to observe the lunchroom. The race and seat location of all students
in the lunchrooms as well as certain information about the schools were recorded (See
Tables 1 and 2 for descriptive statistics of key variables). In total, 4,302 students were
observed, 2,864 from public schools and 1,438 from private schools. Comparisons of the
students observed to aggregate information provided by the public schools suggests that
our sample was representative of the population (aggregate information was not available
for private schools in both cities).

While we are confident that our samples are representative of the
public and private school populations in these two cities, it is always possible that the
two cities are somehow unrepresentative of other cities. Only a nationally representative
sample could fully address these concerns. Nevertheless, there are no obvious differences
between the racial dynamics of these cities and other cities nationwide. It is true that
one of the cities from which subjects were drawn has a large proportion of Latino
students, but many American cities have a plurality or even a majority of minority
students. While some caution should be exercised in extrapolating from these results to
public and private schools in the nation as a whole, we believe that the lack of obvious
differences between these and other cities allows one to make general statements from the
results of this study.

The Results

Of all students observed in private school lunchrooms, 63.5% were in
an integrated setting. That is, 63.5% of private school students were sitting in a group
where at least one of the five students immediately around them was of a different racial
group. In public schools, 49.7% of all students were in a similarly integrated lunchroom
setting (See Table 3). This difference is both substantively and statistically
significant. Private school students are more likely to be sitting in racially
heterogeneous groups than are public school students.

These relatively high-sounding numbers on the extent of integration
may be misleading unless one remembers that the definition of integration only required
that one of five students sitting nearby be of a different racial group. The numbers sound
more bleak if we consider the extent of racially homogeneous lunchroom settings. Slightly
more than a third (36.5%) of private school students sit in groups where everyone is of
the same race. A little more than half (50.3%) of public school students sit entirely
surrounded by people of their own racial group.

The difference between integration in public and private schools is
larger once some of the basic characteristics of schools are controlled statistically.
Because not all public and private school students in our sample shared schools with the
same characteristics, it is possible that some or all of the difference in integration
could be attributed to those characteristics, not the public or private nature of the
school. For example, the number of public and private school subjects in each city was not
even, allowing for the possibility that one city with worse racial relations might skew
the results. Public and private schools also differed slightly in the extent to which
students were assigned to their lunch seats. If seating was assigned or restricted by
class, then the observed integration might be a function of that school policy and not
really an output of positive racial socialization. The size of the school and the grade
level of the students observed also differed in public and private schools. Controlling
for all of these factors (city, seating restrictions, school size, and student grade
level) in a logistic regression yields an adjusted integration result for public and
private school students (See Table 7 for a presentation of all logistic models used in
this paper). As is clear from Table 3, adjusting for all of these differences between
public and private schools produces an even larger integration advantage for private
schools. After adjusting for these factors, 78.9% of private school students are in a
racially heterogeneous lunchroom setting compared to 42.5% of public school students.

These results clearly show that private school students are more
likely to have a positive, integrated school experience than public school students. In
the following sections we will consider possible explanations for this fact, but they do
not alter the fact itself. Regardless of why private schools may better produce
integration, the fact that they do is contrary to widely help assumptions about race and
private schooling and is therefore an important finding.

Possible Explanation: Income and Social Class

Students in private schools may mix more easily with students of
other races because they may have a greater tendency to come from families with higher
incomes and social class. Perhaps the obstacle to racial integration is really class
segregation. Middle and upper-class whites may feel more comfortable mixing with middle
and upper-class minorities than with lower class minorities. Perhaps higher-class students
in general are more favorably inclined to the idea of integration. To the extent that
private schools have students of higher social class and to the extent that integration
level is altered by class, then the private school advantage may be partially or fully
explained by the social class composition of private schools.

To test this explanation, we employ a rough measure of social class.
From public schools we collected information on the percentage of students who receive
free or reduced-price school lunch as an indicator of the average social class in that
school. None of the private schools participated in the government free lunch program, so
collecting comparable data from them was difficult. We simply asked them to estimate the
percentage of their students who would qualify for a lunch program if they had one. As it
turns out, the income limit that private school administrators believed was necessary for
qualifying for a government lunch program is much lower than is actually the case.
Therefore, the estimate of low-income students in private schools is almost certainly an
underestimate. This measure of social class is also limited in other ways. Income and
class are not necessarily the same thing, and moreover, free or reduced price lunch
eligibility is a crude measure of income because it only has two categories.

Despite the limitations of this measure, including free or reduced
price lunch eligibility as a variable in the logit model interestingly does not do much to
close the gap in integration between private and public schools (See Table 3). Controlling
for this rough measure of social class as well as the city, seating restrictions, school
size, and grade-level observed in each school yields an adjusted percentage of 67.5% of
private school students in an integrated setting compared to 49.9% of public school
students. The advantage of private schools at integration is still large and statistically
significant.

Possible Explanation: Mission

Perhaps many private schools produce better results because their
religious mission is conducive to integration. Perhaps the political ideology attached to
many U.S. religions (e.g., we are all equal in the eyes of G-d) prompts religious private
schools to make extra efforts at practices that reflect this ideology, such as
integration. It is also possible that a private schools adherence to a religious or
other strongly held mission may help the parents of that schools students overcome
anxieties about integration. Shared support for the private schools mission may be
an over-arching objective that reduces resistance to mixing with people of other races.

One way to test this explanation is to examine the extent to which
schools with a religious component to their curriculum are better integrated than secular
private schools or secular public schools. A logistic regression that controls for the
same factors as the models above yields the following adjusted rates of integration: 48.9%
of public school students are in integrated settings compared to 44.1% of secular, private
school students and 67.9% of religious, private school students (See Table 4). The
difference between secular public and private schools is not close to being statistically
significant, while the religious private schools are significantly better integrated.

From these results we can conclude that a religious education is
positively related to integration. The existence of an advantage only for religious and
not for secular private schools, however, is a conclusion that is difficult to make with
great confidence from these data. It is difficult to verify this conclusion because of the
limited number of private secular schools in our sample. In addition, private secular
schools would have been significantly better integrated than public schools had we not
controlled for our rough measure of social class. To the extent that the school lunch
measure underestimated the number of low-income students in the secular private schools,
we are underestimating the rate of integration in those schools. Nonetheless, religious
mission appears to be an important component of school success in promoting integration.

Possible Explanation: Segregation in Housing

Private schools may be better integrated than public schools because
they depend less on racially segregated housing patterns for selecting their student body.
Public schools tend to replicate and reinforce racial segregation in housing. Public
policies and private housing decisions have created patterns of racially homogenous
neighborhoods. Because public schools overwhelmingly select their student population based
on where students live, these schools reproduce the racial segregation evident in housing.
(Orfield et al, 1996) Private schools, on the other hand, are only
constrained in the geographic location from which they can draw students by the practical
limits of transportation difficulties.

But if families resist integration in housing, why would they
voluntarily integrate in private schools? By detaching schooling from housing, private
schools may greatly reduce the anxiety that parents feel about the consequences of an
effort at integration that goes badly. For most home-owners their house is their largest,
highly-leveraged, asset. The financial repercussions for those home-owners should the area
in which they reside become undesirable due to problems with local school integration are
enormous. Families must then not only suffer with an undesirable school from which they
cannot easily exit, but they risk losing a large amount of their highly-leveraged asset.
If integration goes poorly in a private school, families suffer no more than the
disruption of moving their child to a different school. They do not have to sell their
house, re-locate, and suffer the financial consequences. By reducing the possible costs of
integration, private schools may make families more open to the benefits of an integrated
education.

Evidence from our analysis strongly supports this explanation. We
collected information on the proportion of students in each public school who lived
outside of the normal attendance zone for that school. This figure would include students
who participate in magnet or other public school choice programs. While fewer than 5% of
all public school students attended schools outside of their attendance zone, we can use a
logit model to simulate how integration would change if a larger proportion of students
attended schools outside of their neighborhood. With just under 5% of students attending
public schools outside of their attendance zones, the Index of Integration is only 49.5%.
But if we statistically increase the number of students who choose schools outside of
their housing area to 50%, the IOI increases to 74.3%. That is, if half of all public
school students came from housing outside of the attendance zone, the percentage of
students who would have racially integrated lunchroom settings would increase to 74.3%.
(See Table 5) By simulating the detachment of housing from schooling in public schools, we
generate an estimated rate of integration in public schools that is comparable to that
observed in private schools.

We can simulate the effect of housing on integration in public
schools in another way as well. When schooling is based primarily on attendance zones, the
size of a school reflects the size of the geographic area from which it draws students. If
we statistically increase the number of students in a school, we can simulate the effect
of including additional neighborhoods in a schools attendance zone. Attendance zones
that cover more neighborhoods would likely decrease the influence of segregated housing on
school integration. Using a logit model of integration in public schools, we can simulate
the importance of expanding current attendance zones on schools by increasing
statistically the number of students in the schools. If we double the average size of the
public schools in our sample from 887 to 1,774, we increase the rate of integration from
49.5% to 82.9%. (See Table 6) Simulating larger schools, thereby modeling the decreased
influence of housing on schooling, shows that integration would be significantly higher if
the specific neighborhood in which one lives did not determine the school to which
ones children must attend.

Conclusion

These simulations can only be suggestive of the influence of
segregation in housing on integration in public and private schools. It may not be
realistic or desirable to increase school size or draw half of school populations from
outside of an attendance zone. But the point is that these simulated effects of housing on
public school integration can generate predicted rates of integration that are comparable
to those found in private schools. This suggests that one of the more important advantages
for private schools in integration is that they do not determine their student population
based on racially segregated housing patterns. The higher social class of students and
strong religious missions of private schools may also contribute to their higher rates of
integration.

Observing a national sample of school lunchrooms and collecting more
detailed information on the class, mission, and housing factors that may influence
integration would allow for stronger conclusions. While not definitive, the evidence
presented here should help redefine how we think about integration in public and private
schools. We should no longer accept unquestioningly the widely held view that public
schools are better at integration than private schools. We should seriously consider
policy proposals that would detach schooling from housing. This could include magnet
schools and other public school choice programs as well as school choice programs that
include private schools. If we include private schools in choice programs we should
seriously consider including religious schools among the available options because the
religious mission of those schools may further advance racial integration in schools. In
short, if we are serious about the benefits of racially heterogeneous school experiences,
we need to consider abandoning or modifying the long held view that the traditional public
schools is equivalent to the ideal of the common school.

Table 1: Descriptive Statistics for all Public and Private School Subjects

Variables

N

Mean

Std
Deviation

City

4302

.547

.4978

Private school

4302

.3343

.4718

Seating restrictions

(Students assigned or restricted in where they sit)

4302

.3357

.4723

School size

(Total number of students in school)

4302

723.4035

370.9198

Student grade level

(Average grade observed in lunchroom)

4302

5.1738

3.3235

Low-income

(Percent receiving free or reduced-price lunch)

4253*

51.5126

38.9063

Religious
curriculum

(Students attending school with religious
curriculum)

4302

.31

.46

Index of Integration

(likelihood of sitting in a racially heterogeneous group)

4302

.5430

.4982

*N for this variable is smaller
because one private school did not provide information.

Table 2:
Descriptive Statistics for Public School Subjects

Variables

N

Mean

Std
Deviation

City

2864

.5168

.4998

Seating restrictions

(Students assigned or restricted in where they sit)

2864

.4330

.4956

School Size

(Total number of students in school)

2864

886.9679

333.0814

Student grade level

(Average grade observed in lunchroom)

2864

4.7291

3.0681

Low-income

(Percent receiving free or reduced-price lunch)

2864

73.2124

26.9376

Zoned

(Percent living in school attendance zone)

2864

95.1166

8.3727

Index of Integration

(Likelihood of sitting in a racially heterogeneous group)

2864

.4969

.5001

Table 3:
Rates of Integration in Public and Private Schools

Measure

Public

Private

Index of Integration (IOI)

49.7%

63.5%

IOI, Adjusted for effect of
city,

seating restrictions, school size,

student grade level

42.5%

78.9%

IOI, Adjusted for effect of
city,

seating restrictions, school size,

student grade level, and income

49.9%

67.5%

Table 4:
Effect of Religious Mission on Integration in Public and Private Schools

Measure

Public

Private,
Secular

Private,
Religious

Index of Integration (IOI),

Adjusted for effect of city,

seating restrictions, school size, income,

student grade level

48.9%

44.1%

67.9%

Table 5:
Simulated Effect of Increasing Student Population in Public Schools Drawn from Outside of
School Attendance Zone

Table
7: Regression Results Derived from Logistic Models of the Effect of Various Factors on
Integration

Variable

Model 1

Model 2

Model 3

Model 4

Constant

.2741

1.0758*

1.1604*

2.4587*

(.1546)

(.1990)

(.2008)

(.5534)

City

-.0754

.2054*

.1914*

.1149

(.0664)

(.0779)

(.0780)

(.0965)

Private

1.6216*

.7340*

-.1927

(.1393)

(.1918)

(.3078)

Seating restrictions

.0162

.0460

-.0025

.0350

(.0866)

(.0877)

(.0888)

(.1196)

School size

.0012*

.0012*

.0011*

.0018*

(.0002)

(.0002)

(.0002)

(.0003)

Student grade level

-.2722*

-.2760*

-.2840*

-.3948*

.0149

(.0160)

(.0162)

(.0288)

Low-income

-.0126*

-.0123*

(.0017)

(.0017)

Zoned

-.0240*

(.0056)

How religious

.9851*

(.2579)

N

4253

4253

4253

2864

*significant at the p
<.05 level

standard errors are in parentheses

Models 1 is the logistic regression used to compute the
first set of adjusted Index of Integration results presented in row 2 of Table 3. Model 2
was used to compute the second set of adjusted IOI results (controlling for income as
well) that are presented in row 3 of Table 3. Model 3 was used to compute the IOI results
in Table 4, which presents the effect of religious curriculum on integration. And Model 4,
which draws only on public school data, was used to calculate IOI results for Tables 5 and
6 on the simulated effect of changing public school attendance zone practices.

References

Armor, David. 1995. Forced Justice: School
Desegregation and the Law. New York: Oxford University Press.

Where Bi and Wi are equal to the number of
blacks and whites in the ith school and B and W are equal to the number of
African-American and white students in the district as a whole (African-American and white
students are used for this illustration although any two ethnic or racial groups could
obviously be compared).

Social scientists use this formula to calibrate the degree of racial
imbalance within a particular school district, with 0 representing perfect desegregation
(or balance) and 1 representing a perfectly segregated district (Duncan and Duncan 1955,
Taueber 1965, Crain, et al. 1984, Rossell 1990).

Where Bi is equal to the number of African-Americans
in the ith school, wi is the percentage white in that school, and w is, the percentage
white in the district as a whole (again using African-American and white categories for
ease of discussion, though any two groups could be compared). The score generated by this
formula is interpreted as the percentage white in the average African-American
students school in that particular school district. To calculate the percentage
African-American in the average white students school, one would simply need to
substitute percentage African-American for percentage white and vice versa (Crain 1984,
Rossell 1990).

Where Ewb is the unstandardized IOE and w is
the percentage white in the district as a whole.

5. Two public schools and two
private schools declined to participate. One additional public and one additional
private school were then randomly selected to partially replace the schools that declined
to participate. Because the rate of decline was both low and evenly split between the
sectors, we have no reason to believe that our results have been biased by non-compliance.

6. In a 1996 study, Gary
Orfield, et al., found that the nations public school districts are accelerating
away from desegregation goals by returning to the practice of "neighborhood" or
zoned schools, which effectively re-segregate students along segregated housing lines. He
argues that this is a result of legal and legislative actions that have excused districts
from federal oversight once they are declared unitary (i.e. no longer operating a dual,
segregated, educational structure).

This article is Copyright ? 1998 by Jay P. Greene and Nicole
Mellow. It is reproduced here by permission of the authors. All rights reserved.